1. Field of the Invention
The present invention relates to an ultrasonic image processing apparatus, and more particularly to technology for enhancing the image quality of a three-dimensional ultrasonic image.
2. Description of Related Art
An ultrasonic image processing apparatus is an apparatus which forms an ultrasonic image based on data acquired by transmission and reception of ultrasound or which processes such an ultrasonic image, and is configured as an ultrasonic diagnosis apparatus or an information processing apparatus. Here, an information processing apparatus is a computer which processes data transmitted from an ultrasonic diagnosis apparatus, for example. In an ultrasonic image processing apparatus, an ultrasonic image to be formed or to be processed includes a two-dimensional ultrasonic image, a three-dimensional ultrasonic image, or the like.
By applying a volume rendering method to volume data (a set of echo data) acquired from a three-dimensional space within a living organism (a living body), a three-dimensional ultrasonic image (a volume rendering image) is formed. More specifically, first, a plurality of rays (virtual lines of sight, which correspond to an operation path) extending from a point of view are set with respect to the volume data, and then a predetermined operation is executed in a repeated manner sequentially for sample points existing on each of the rays, thereby obtaining a pixel value for each ray. Finally, a three-dimensional image is formed as a set of a plurality of pixel values corresponding to the plurality of rays. (See JP 10-33538 A, for example.)
The algorithm of general volume rendering is expressed by the following formula. In the following formula, I represents a pixel value (a brightness value), e(i) represents an echo intensity (an echo value) on a sample point on a ray, and o(e(i)) represents the opacity (a degree of opaqueness), in which i represents the number of a sample point.I=Σ[e(i)*o(e(i))*(1−o_out(i−1))]  (1)
wherein o_out(i)=Σo(e(i))*(1−o_out(i−1))
Here, the operation is completed when the sum of the opacities reaches 1 or when the sample point is outside the operation range, and the value of I at this time is mapped on a projection plane. The above formula (1) is only an example, and various other algorithms for the volume rendering processing are known.
Here, as the display methods for a three-dimensional image, there are known a four-view display in which four images are displayed within a single screen (e.g. display of three orthogonal cross-sectional images and a 3D image), a two-view display in which two images are displayed within a single screen (e.g. display of a cross-sectional image and a 3D image), a one-view display in which a single image is displayed within a single screen (e.g. display of a 3D image), or the like. As the time required for processing single volume data is generally in proportion to the number of pixels on the projection plane (i.e. the number of rays), among the three methods described above, the one-view display method requires the longest processing time. The larger the monitor size, as the number of pixels forming the display image increases, the processing time becomes longer accordingly. As such, in general, there is a problem concerning formation of a three-dimensional image in that the amount of computation is large and the burden on the CPU is large. While the use of high-speed processors can be considered, in this case, another problem of increased cost would also arise.
While it is desirable to reduce the number of rays to thereby decrease the amount of computation in order to deal with the above problems, if the number of rays is simply decreased, the resolution of the three-dimensional image is lowered or the size of the three-dimensional image is reduced. Application of linear interpolation processing can therefore be considered. With the linear interpolation processing, it is possible to increase the apparent number of pixels and the resolution. This processing, however, causes the image to be blurred, which leads to a problem of a reduction in image quality. The problem of reduction in image quality would also arise when an image is simply enlarged.
It is generally pointed out that a three-dimensional ultrasonic image generated by the volume rendering method lacks sharpness and has unclear contours. Here, the conventional general interpolation processing references four, eight, or sixteen vicinity pixels existing around a noted pixel. In other words, in the conventional general interpolation processing, the range to be referenced extends equally in all directions around the noted pixel. In the conventional art, it is not possible to adaptively change the interpolation condition in accordance with the structure of a tissue.
JP 2010-125 A discloses an apparatus for forming an image of cartilage included in the knee joint. This reference describes, starting from paragraph 0042, the contents of pre-processing which is executed prior to the cartilage image forming processing. The pre-processing is executed in units of slice data (two-dimensional frames). More specifically, among a plurality of line segments extending through a noted pixel, a line segment having the maximum dispersion value is specified and a line segment which is orthogonal to that specified line segment is further specified. Then, an average value of a plurality of pixel values existing on that orthogonal line segment is calculated and is used as an updated pixel value for the noted pixel. This processing is applied to each slice data before formation of a cartilage image, and therefore is not processing which is applied to a 3D image after the volume rendering. Further, JP 2010-125 A does not describe special directional interpolation processing having a magnification changing function (a resolution changing function).